149 resultados para Análise de desempenho


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Ensuring the dependability requirements is essential for the industrial applications since faults may cause failures whose consequences result in economic losses, environmental damage or hurting people. Therefore, faced from the relevance of topic, this thesis proposes a methodology for the dependability evaluation of industrial wireless networks (WirelessHART, ISA100.11a, WIA-PA) on early design phase. However, the proposal can be easily adapted to maintenance and expansion stages of network. The proposal uses graph theory and fault tree formalism to create automatically an analytical model from a given wireless industrial network topology, where the dependability can be evaluated. The evaluation metrics supported are the reliability, availability, MTTF (mean time to failure), importance measures of devices, redundancy aspects and common cause failures. It must be emphasized that the proposal is independent of any tool to evaluate quantitatively the target metrics. However, due to validation issues it was used a tool widely accepted on academy for this purpose (SHARPE). In addition, an algorithm to generate the minimal cut sets, originally applied on graph theory, was adapted to fault tree formalism to guarantee the scalability of methodology in wireless industrial network environments (< 100 devices). Finally, the proposed methodology was validate from typical scenarios found in industrial environments, as star, line, cluster and mesh topologies. It was also evaluated scenarios with common cause failures and best practices to guide the design of an industrial wireless network. For guarantee scalability requirements, it was analyzed the performance of methodology in different scenarios where the results shown the applicability of proposal for networks typically found in industrial environments

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The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

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Este trabalho apresenta um levantamento dos problemas associados à influência da observabilidade e da visualização radial no projeto de sistemas de monitoramento para redes de grande magnitude e complexidade. Além disso, se propõe a apresentar soluções para parte desses problemas. Através da utilização da Teoria de Redes Complexas, são abordadas duas questões: (i) a localização e a quantidade de nós necessários para garantir uma aquisição de dados capaz de representar o estado da rede de forma efetiva e (ii) a elaboração de um modelo de visualização das informações da rede capaz de ampliar a capacidade de inferência e de entendimento de suas propriedades. A tese estabelece limites teóricos a estas questões e apresenta um estudo sobre a complexidade do monitoramento eficaz, eficiente e escalável de redes

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This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities

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ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

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In this work, a performance analysis of transmission schemes employing turbo trellis coded modulation. In general, the performance analysis of such schemes is guided by evaluating the error probability of these schemes. The exact evaluation of this probability is very complex and inefficient from the computational point of view, a widely used alternative is the use of union bound of error probability, because of its easy implementation and computational produce bounds that converge quickly. Since it is the union bound, it should use to expurge some elements of distance spectrum to obtain a tight bound. The main contribution of this work is that the listing proposal is carried out from the puncturing at the level of symbol rather than bit-level as in most works of literature. The main reason for using the symbol level puncturing lies in the fact that the enummerating function of the turbo scheme is obtained directly from complex sequences of signals through the trellis and not indirectly from the binary sequences that require further binary to complex mapping, as proposed by previous works. Thus, algorithms can be applied through matrix from the adjacency matrix, which is obtained by calculating the distances of the complex sequences of the trellis. This work also presents two matrix algorithms for state reduction and the evaluation of the transfer function of this. The results presented in comparisons of the bounds obtained using the proposed technique with some turbo codes of the literature corroborate the proposition of this paper that the expurgated bounds obtained are quite tight and matrix algorithms are easily implemented in any programming software language

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They are in this study the experimental results of the analysis of thermal performance of composite material made from a plant matrix of polyurethane derived from castor oil of kernel of mamona (COF) and loading of clay-mineral called vermiculite expanded. Bodies of evidence in the proportions in weight of 10%, 15% and 20% were made to determine the thermal properties: conductivity (k), diffusivity (ά) and heat capacity (C), for purposes of comparison, the measurements were also performed the properties of polyurethane of castor without charge and also the oil polyurethane (PU), both already used in thermal insulation. Plates of 0.25 meters of material analyzed were manufactured for use as insulation material in a chamber performance thermal coverage. Thermocouples were distributed on the surface of the cover, and inside the material inside the test chamber and this in turn was subjected to artificial heating, consisting of a bank of incandescent lamps of 3000 w. The results obtained with the composite materials were compared with data from similar tests conducted with the camera alone with: (a) of oil PU, (b) of COF (c) glass wool, (d ) of rock wool. The heat resistance tests were performed with these composites, obtaining temperature limits for use in the range of 100 º C to 130 º C. Based on the analysis of the results of performance and thermal properties, it was possible to conclude that the COF composites with load of expanded vermiculite present behavior very close to those exhibited by commercial insulation material

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This work proposes the development of an innovative material made from a vegetable polyurethane matrix and load of industrial waste, from retread tires, for thermal insulation and environmental comfort. Experimental procedures are presented, as well as the results of the thermal and acoustic performance of this composite material, made from an expansive foam derived from the castor seed oil and fiber of scrap tires. The residue was treated superficially with sodium hydroxide, to eliminate contaminants, and characterized macroscopically and microscopically. Samples were produced with addition of residues at levels of 5%, 10%, 15% and 20% by weight, for determination of thermal properties: conductivity, heat capacity and thermal diffusivity, sound absortion index and density. The results were compared to commercially available thermal insulation and sound absorbing products. According to the analysis of results, it was concluded that the developed composite presents characteristics that qualify it as a thermal insulation with superior performance, compared to commercial available insulation, and sound absorption capacity greater than the castor oil polyurethane s, without addition of the residue

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In Natal/RN, 68% of the population uses some kind of individual system for their domestic sewers treatment, being that the most used it is septic tank, followed by sumidouro. Every treatment system of sewers, usually used, generates a by-product denominated sludge. That residue presents some components, in its constitution, undesirable under the environmental and sanitary point of view. In such case, to assure that the system treatment has satisfactory results, it is necessary to do the adjusted disposition of the sludge sewage. Several countries are looking for technical alternatives for the use and disposition of residues. Under technical and environmental conditions appropriate, these materials can be used, decreasing the consumption of the natural resources and the treatment need, storage or elimination of the wastes, what decrease the risks created. Some of the alternatives of recycling of the sludge sewage are: the application in the agriculture, in the production of energy and as raw material in the civil construction. This study evaluated asphalt mixtures behavior that partially substituted conventional aggregates by septic tank sludge. The septic tank sludge gave origin to two raw materials called raw sludge and sludge ash. The raw sludge was put as a small aggregate and the sludge ash as filler. In the first experiment it was made a comparison between the mixture with conventional aggregates and the mixtures that replaced sand by raw sludge in the proportions from 5% to 40%. In the second experiment, it was made comparison between mixtures with 1%, 2% and 3% of sludge ash and cement. The stages developed along the study were: physical characterization of the conventional materials; physical, chemistry, thermal, mineralogical characterizations and analysis of environmental risk of the raw sludge; physical characterization and analysis of environmental risk of the sludge ash; analysis of the mixtures performance through its volumetric and mechanical characteristics; forecast of the mixtures susceptibility in the moisture presence. For the grain size composition used and with the percentage asphalt adopted, the mixtures with up to 7,5% of raw sludge in his composition attend to the National Department of Transports Infrastructure (DNIT) specifications. However, in agreement with the mixtures susceptibility in the moisture presence, the mixtures with addition of raw sludge don't present satisfactory acting. In such case, they could be used in arid and semi-arid areas. The raw sludge application in mixtures increased their voids volume and their stability. However, it damaged mixtures adhesiveness. Mixtures with sludge ash and with cement presented similar behavior. However, mixtures with sludge ash presented a better performance than mixtures with cement as for their stability and their tensile strength ratio. The mixture with 1% of sludge ash is better. The wastes studied don't represent environmental risk

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The behavior of bullfrogs reared in captivity must be well understood to support management practices that use efficient feeding regimes. In general, bullfrogs reared in captivity have normal pigmentation, but to develop an enhanced product, some studies have investigated the introduction of albino individuals in frog farms. The present study characterized the behavior of both pigmented and albino bullfrogs reared in captivity. In an initial experiment, 48 bullfrogs (70.5 ± 25.6 g) housed in small stalls were fed once a day at random times. Frogs were filmed and the images showed that both the pigmented and albino varieties behaved similarly: food intake was more frequent at dawn followed by light periods; moving and resting in dry areas may be associated to feeding events; frogs appeared to anticipate feeding time and to rest in the water more frequently in periods other than feeding time; daylight is the recommended period for feeding both pigmented and albino frogs. In a second experiment, 72 albino bullfrogs were fed at fixed times (10 a.m. or 4 p.m.) in small stalls. An initial weight of 23.8 ± 7.6 g was considered to evaluate frog performance, and after the animals reached 60.0 ± 20.0 g, they were filmed for behavior analyses. Food intake varied as a function of feeding time, and frogs were more likely to eat during the early hours of the day and immediately after receiving fresh food. Frogs fed only in the afternoon changed their behavior. Food supplied twice a day stimulated the albino frogs to eat at different times, but did not increase growth. Although fresh food stimulated feeding behavior, food intake was more frequent at dawn. Food supplied at this time of day should therefore be further investigated. The results did not indicate a more suitable feeding time (10 a.m. or 4 p.m.) for albino bullfrogs, or any advantage in using two feedings per day. The results provide xvi important information about bullfrogs in terms of food supply regime and activity preferences throughout the day. This novel information will contribute to future studies in this area

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The Quadratic Minimum Spanning Tree Problem (QMST) is a version of the Minimum Spanning Tree Problem in which, besides the traditional linear costs, there is a quadratic structure of costs. This quadratic structure models interaction effects between pairs of edges. Linear and quadratic costs are added up to constitute the total cost of the spanning tree, which must be minimized. When these interactions are restricted to adjacent edges, the problem is named Adjacent Only Quadratic Minimum Spanning Tree (AQMST). AQMST and QMST are NP-hard problems that model several problems of transport and distribution networks design. In general, AQMST arises as a more suitable model for real problems. Although, in literature, linear and quadratic costs are added, in real applications, they may be conflicting. In this case, it may be interesting to consider these costs separately. In this sense, Multiobjective Optimization provides a more realistic model for QMST and AQMST. A review of the state-of-the-art, so far, was not able to find papers regarding these problems under a biobjective point of view. Thus, the objective of this Thesis is the development of exact and heuristic algorithms for the Biobjective Adjacent Only Quadratic Spanning Tree Problem (bi-AQST). In order to do so, as theoretical foundation, other NP-hard problems directly related to bi-AQST are discussed: the QMST and AQMST problems. Bracktracking and branch-and-bound exact algorithms are proposed to the target problem of this investigation. The heuristic algorithms developed are: Pareto Local Search, Tabu Search with ejection chain, Transgenetic Algorithm, NSGA-II and a hybridization of the two last-mentioned proposals called NSTA. The proposed algorithms are compared to each other through performance analysis regarding computational experiments with instances adapted from the QMST literature. With regard to exact algorithms, the analysis considers, in particular, the execution time. In case of the heuristic algorithms, besides execution time, the quality of the generated approximation sets is evaluated. Quality indicators are used to assess such information. Appropriate statistical tools are used to measure the performance of exact and heuristic algorithms. Considering the set of instances adopted as well as the criteria of execution time and quality of the generated approximation set, the experiments showed that the Tabu Search with ejection chain approach obtained the best results and the transgenetic algorithm ranked second. The PLS algorithm obtained good quality solutions, but at a very high computational time compared to the other (meta)heuristics, getting the third place. NSTA and NSGA-II algorithms got the last positions

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This work presents a proposal of a multi-middleware environment to develop distributed applications, which abstracts different underlying middleware platforms. This work describes: (i) the reference architecture designed for the environment, (ii) an implementation which aims to validate the specified architecture integrating CORBA and EJB, (iii) a case study illustrating the use of the environment, (iv) a performance analysis. The proposed environment allows interoperability on middleware platforms, allowing the reuse of components of different kinds of middleware platforms in a transparency away to the developer and without major losses in performance. Also in the implementation we developed an Eclipse plugin which allows developers gain greater productivity at developing distributed applications using the proposed environment

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The increase of applications complexity has demanded hardware even more flexible and able to achieve higher performance. Traditional hardware solutions have not been successful in providing these applications constraints. General purpose processors have inherent flexibility, since they perform several tasks, however, they can not reach high performance when compared to application-specific devices. Moreover, since application-specific devices perform only few tasks, they achieve high performance, although they have less flexibility. Reconfigurable architectures emerged as an alternative to traditional approaches and have become an area of rising interest over the last decades. The purpose of this new paradigm is to modify the device s behavior according to the application. Thus, it is possible to balance flexibility and performance and also to attend the applications constraints. This work presents the design and implementation of a coarse grained hybrid reconfigurable architecture to stream-based applications. The architecture, named RoSA, consists of a reconfigurable logic attached to a processor. Its goal is to exploit the instruction level parallelism from intensive data-flow applications to accelerate the application s execution on the reconfigurable logic. The instruction level parallelism extraction is done at compile time, thus, this work also presents an optimization phase to the RoSA architecture to be included in the GCC compiler. To design the architecture, this work also presents a methodology based on hardware reuse of datapaths, named RoSE. RoSE aims to visualize the reconfigurable units through reusability levels, which provides area saving and datapath simplification. The architecture presented was implemented in hardware description language (VHDL). It was validated through simulations and prototyping. To characterize performance analysis some benchmarks were used and they demonstrated a speedup of 11x on the execution of some applications

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This work approaches the Scheduling Workover Rigs Problem (SWRP) to maintain the wells of an oil field, although difficult to resolve, is extremely important economical, technical and environmental. A mathematical formulation of this problem is presented, where an algorithmic approach was developed. The problem can be considered to find the best scheduling service to the wells by the workover rigs, taking into account the minimization of the composition related to the costs of the workover rigs and the total loss of oil suffered by the wells. This problem is similar to the Vehicle Routing Problem (VRP), which is classified as belonging to the NP-hard class. The goal of this research is to develop an algorithmic approach to solve the SWRP, using the fundamentals of metaheuristics like Memetic Algorithm and GRASP. Instances are generated for the tests to analyze the computational performance of the approaches mentioned above, using data that are close to reality. Thereafter, is performed a comparison of performance and quality of the results obtained by each one of techniques used

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In Brazil, the selection of school principals is set in a decentralized manner by each state and city, such that processes may vary with time for a specific locality. In the state of Bahia, school principals were appointed by a higher political hierarchy until 2008, when schools under state administration started selecting principals by elections. The main goal of this work is to evaluate whether changing this specific rule affected students proficiency levels. This is achieved by using a panel data and difference-in-differences approachs that compares state schools (treatment group) to city schools (control group) that did not face a selection rule change and thus kept having their principals politically appointed. The databases used are Prova Brasil 2007, 2009 and 2011, the first one prior and the other two former to the policy change. Our results suggest that students attending schools with principals that are selected and elected have slightly lower mean proficiency levels both in mathematics and in portuguese exams than those attending schools with appointed principals. This result, according to the literature, could be related to perverse effects of selecting school administrators by vote, such as corporatism, clientelism and politicization of the school environment